The Complimentary Functions of Minor Characters to Shakespeare's Themes

本文通过对莎士比亚四大悲剧文本的细致分析,探讨了莎剧中小人物对莎氏悲剧主题的作用,指出其有两点作用:一、揭示主题;二、深化主题。

Characters of Temperature Variation and Minimal Temperature Forecast inside of Solar Greenhouse in Winter in Shouguang City of Shandong Province

[Objective] The aim was to improve meteorological service of protected agriculture and to reduce effects of meteorological disasters. [Method] Characters of temperature variation in solar greenhouse and minimal temperature forecast models in winter were analyzed based on meteorological data inside and outside of solar greenhouse in winter during 2008-2011, as per correlation and stepwise regression method. [Result] Temperature was of significant changes in solar greenhouse in sunny and cloudy days and the change was higher in sunny days. In overcast days, temperature in solar greenhouse was lower and plants were affected seriously. In addition, the minimal temperature was of good correlation with outside temperature and humidity, temperature and soil temperature in greenhouse. [Conclusion] The minimal temperature forecast model of solar greenhouse is established and the average absolute error of the forecasted minimums in different types of weather was less than 1 ℃ and the average relative error was lower than 10%.

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

A Method for Detecting and Recognizing Yi Character Based on Deep Learning

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with other typical algorithms.In these comparisons,the proposed model achieves better detection and recognition results with a certain reliability.

Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters Recognition Model

Handwritten character recognition becomes one of the challenging research matters.More studies were presented for recognizing letters of various languages.The availability of Arabic handwritten characters databases was confined.Almost a quarter of a billion people worldwide write and speak Arabic.More historical books and files indicate a vital data set for many Arab nationswritten in Arabic.Recently,Arabic handwritten character recognition(AHCR)has grabbed the attention and has become a difficult topic for pattern recognition and computer vision(CV).Therefore,this study develops fireworks optimizationwith the deep learning-based AHCR(FWODL-AHCR)technique.Themajor intention of the FWODL-AHCR technique is to recognize the distinct handwritten characters in the Arabic language.It initially pre-processes the handwritten images to improve their quality of them.Then,the RetinaNet-based deep convolutional neural network is applied as a feature extractor to produce feature vectors.Next,the deep echo state network(DESN)model is utilized to classify handwritten characters.Finally,the FWO algorithm is exploited as a hyperparameter tuning strategy to boost recognition performance.Various simulations in series were performed to exhibit the enhanced performance of the FWODL-AHCR technique.The comparison study portrayed the supremacy of the FWODL-AHCR technique over other approaches,with 99.91%and 98.94%on Hijja and AHCD datasets,respectively.

Audio2AB:Audio-driven collaborative generation of virtual character animation

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of success.However,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient attention.Methods Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body animations.This parameterization method can be used to drive full-body animations of virtual characters and improve their portability.In the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial data.The Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio features.Finally,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss function.Results By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape weights.Therefore,different 3D virtual character animations could be created through parameterization.Conclusions The experimental results showed that the proposed method could generate significant gestures and facial animations.

A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.

The shape character and development stage of nebkha

Based on statistical analysis on morphological data of nebkhas surveyed in the Hotan River Basin,Xinjiang, the changing regularity and characters of nebkhas’ morphology in different development stageshave been discussed. Results indicate that there exist better correlation among length, width and altitudeof all kinds of nebkhas, but there are certain various shape characters in different nebkhas and the sametype of nebkhas in differential development stages. On account of analysis on mathematical imitation ofnebkhas’ shape characters, regional ecological environmental and aeolian characters, the development ofthe nebkha can be divided into a growing stage, a stabilizing stage and a declining stage.

Frontier Progress of Landscape Character Assessment in China

The role of Landscape Character Assessment(LCA)at the level of territorial landscape governance spans both natural and social sciences.By analyzing the development history,research distribution,methods and applications of cutting-edge cases of LCA in China,the following conclusions are drawn:①the LCA research in China originated earlier than that in Europe,but has not yet been systematically applied to the implementation of urban and rural planning at all levels;②the fundamental theory of LCA in China has been well constructed,with three main research directions:technologyled,assessment-led,and assessment combined with other theories;③the development of LCA in rural areas is more mature than in urban areas,but the progress of research is uneven across regions;④the current research presents significant“bottom-up”academic characteristics,and there is an urgent need for government decision-making authorities and academia to jointly promote a“top-down”standardized governance mechanism to comprehensively promote the modernization of territorial landscape governance.

On the Tragic Character——Miss Havisham in Great Expectations

Charles Dickens,as one of the greatest critical realistic writers in the 19th century,is renowned all around the world.Miss Havisham in Great Expectations is certainly one of the most strange and memorable characters.This paper tries to analyze different aspects of Miss Havisham’s character to explore her tragic life.

Progress in the evaluation tool of Character Strengths and its application in nursing staff

Character Strengths is a group of positive personality traits reflected through cognition,behavior,and emotion,which play a positive role in improving happiness,alleviating negative emotions,and maintaining physical and mental health.This article reviews the concept,content,methods,evaluation tools,and application progress of Character Strengths in nurses,so as to provide a reference for clinical managers and improve the quality of life,mental health,and professional satisfaction of n urses.

Chip Surface Character Recognition Based on OpenCV

Chip surface character recognition is an important part of quality inspection in the field of microelectronics manufacturing.By recognizing the character information on the chip,automated production,quality control,and data collection and analysis can be achieved.This article studies a chip surface character recognition method based on the OpenCV vision library.Firstly,the obtained chip images are preprocessed.Secondly,the template matching method is used to locate the chip position.In addition,the surface characters on the chip are individually segmented,and each character image is extracted separately.Finally,a Support Vector Machine(SVM)is used to classify and recognize characters.The results show that this method can accurately recognize the surface characters of chips and meet the requirements of chip quality inspection.

A Review of Research on Handwritten Chinese Character Recognition with Multi-Feature Fusion

This paper analyzes the progress of handwritten Chinese character recognition technology,from two perspectives:traditional recognition methods and deep learning-based recognition methods.Firstly,the complexity of Chinese character recognition is pointed out,including its numerous categories,complex structure,and the problem of similar characters,especially the variability of handwritten Chinese characters.Subsequently,recognition methods based on feature optimization,model optimization,and fusion techniques are highlighted.The fusion studies between feature optimization and model improvement are further explored,and these studies further enhance the recognition effect through complementary advantages.Finally,the article summarizes the current challenges of Chinese character recognition technology,including accuracy improvement,model complexity,and real-time problems,and looks forward to future research directions.

Mutagenic Improvement of Shattering Characteristic of the Restorer Line of a Hybrid Rice“Xieyou 9308”

The newly developed hybrid rice combination 'Xieyou 9308' (Xieqingzao A/T9308) has been regarded as a super-high-yielding rice variety, of which the yield potential reached as high as 12 t/ha. However, its high shattering characteristic (as high as 60%) has limited its wider application. In the current experiment, a non-shattering mutant line, M9308, was developed from T9308 by gamma irradiation. Comparisons were made but no marked differences were found between T9308 and M9308 as well as between their F1 hybrids crossed to Xieqingzao A for major agronomic and grain quality characters as well as resistance to diseases. Genetic analysis indicated that the non-shattering character of M9308 was governed by a single recessive gene.

Animation of Chinese Characters： Evolution of Shapes and Styles

Hanzi （Chinese characters） has a long history and affluent contents. To promote the popularity of historical and cultural knowledge of Chinese characters, an online program has been launched by Beihang University and Beijing Normal University to explain Chinese characters＇ original meanings and evolution processes with vivid and expressive animation videos. Currently, More than 1,000 videos can be accessed through the website “http：//www.chinesecharacter.org/”. Besides these online resources, a human-computer interaction system is also proposed to simulate clerical changes of Chinese characters through computer morphing technology. What we want is to make the teaching and learning of Chinese characters more reasonable, more easily understandable and more interesting.

Character shaping in animation performance

At present, China＇s animation industry is developing rapidly, the performance of the animation is through a series of design to complete, through the action to create the role of animation characters, which led to the audience resonance. This article mainly analyzes the influencing factors of character creation and the importance of characterization in characterization in the animation performance, and then explores the performance of the characterization in the animation performance. Hoping to through this theoretical study, the animation performance of the characterization of a deeper understanding.

Genetic and Correlation Analysis of Grain Characters in Three-line Hybrid Rice

Abst[Objective] This study was to understand the genetic dynamics of three-line hybrid rice, and explore the respective effect of sterile line and restoring line on grain characters of hybrid rica. [Method] Four three-line stedle lines and 27 restoring lines（cultivars） commonly culti- vated in Central China region were regarded as expadmental materials to conduct 4 x27NCII cross design, and the grain characters of three-line hybrid rico were analyzed at genetic and correlation levels. [ Result] Four characters of grain length, grain width, 1 000-grain weight and length- width ratio play the leading role in additive gene effect; these four characters were simultaneously influenced by male parent and female parent, but the effect from male parent was relatively larger. The grain length, grain width, 1 000-grain weight and length-width ratio all have high brood hedtabUities（ respectively 99.65%, 98.31%, 95.27% and 98.81% ）. Correlation analysis showed that grain length was positively correlated with 1 000-grain weight and length-width ratio at extremely significant level; 1 000-grain weight was positively correlated with grain length and length- width ratio at extremely significant level, and was insignificantly correlated with grain width; grain width was negatively correlated with grain length and length-width ratio at extremely significant level. Path analysis showed that the direct path coefficients of grain length, grain width and 1 0（30- grain weight to length-width ratio were 0.624 6, -0.555 9 and -0.015 8, respectively. [ Conclusion] This study systematically analyzed the effects of stedle line and restoring line on grain characters of hybrid rice, which provided theoretical basis for breeding high quality and yield hy- brid dce.